Paper Citation Record · LEDGER

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition

As of 8 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2607.24030.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2607.24030 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-31T23:18:50.426170Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

37 of 37 outbound references displayed

verified exact2
verified fuzzy0
unresolved35
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 563db763-5073-423b-bc80-f2cb4c3ac2a9 · outbound

This paper cites XLS-R: Self-supervised cross-lingual speech representation learning at scale.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition XLS-R: Self-supervised cross-lingual speech representation learning at scale

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:46.139860Z

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Unavailable: canonical work link unavailable.

Observation 853f18bb-31eb-448c-be88-71eaa28c79fe · outbound

This paper cites Mixture of LoRA experts for low- resourced multi-accent automatic speech recognition.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition Mixture of LoRA experts for low- resourced multi-accent automatic speech recognition

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:46.261003Z

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Observation 7f453f6b-e873-4707-9186-c4a56246d288 · outbound

This paper cites Unsupervised cross-lingual representation learning for speech recognition.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition Unsupervised cross-lingual representation learning for speech recognition

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:46.575384Z

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Observation 3876eb98-575d-440c-bdd8-0a9406e17b90 · outbound

This paper cites FLEURS: Few-shot learning evaluation of universal representations of speech.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition FLEURS: Few-shot learning evaluation of universal representations of speech

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:46.707608Z

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Observation bb9a3e79-520a-40e2-a69b-a62eff03094e · outbound

This paper cites Each plot is annotated with ISO 639-3 language codes following the Ethnologue4 convention.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition Each plot is annotated with ISO 639-3 language codes following the Ethnologue4 convention

Reference 7

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Observation 053fdd58-4404-474a-bbdb-0d2a6cee0dc9 · outbound

This paper cites Mahadeva Prasanna, Deepu Vijayasenan, and Sriram Ganapathy.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition Mahadeva Prasanna, Deepu Vijayasenan, and Sriram Ganapathy

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:47.339346Z

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Observation 04b310bc-b262-4782-9247-bbf401342e2d · outbound

This paper cites Siva Kalyan and Alexandre Franc ¸ois.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition Siva Kalyan and Alexandre Franc ¸ois

Reference 12

Resolution: verified exact; doi, observed 2026-07-31T23:20:57.237139Z

Source-reported events for the cited work

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Observation ef7854fe-e920-4494-b7eb-867ac281482e · outbound

This paper cites Group then scale: Dy- namic mixture-of-experts multilingual language model.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition Group then scale: Dy- namic mixture-of-experts multilingual language model

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:47.694095Z

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Observation 69ce8efd-da60-4b50-8e62-a1ac5628d556 · outbound

This paper cites A first south african corpus of multilingual code-switched soap opera speech.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition A first south african corpus of multilingual code-switched soap opera speech

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:47.902633Z

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Observation 07b7fa48-005c-442f-8c5b-20ee42f1e34d · outbound

This paper cites Attentive statistics pooling for deep speaker embedding.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition Attentive statistics pooling for deep speaker embedding

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:47.963417Z

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Observation b65d0c44-de55-4c49-aae6-ffe72c66b50e · outbound

This paper cites OWSM v4: Improving open Whisper-style speech models via data scaling and cleaning.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition OWSM v4: Improving open Whisper-style speech models via data scaling and cleaning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:48.108564Z

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Observation 5826905a-b03b-4f4b-92ef-85d372535aa0 · outbound

This paper cites RomanLens: The role of latent Romanization in multilinguality in LLMs.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition RomanLens: The role of latent Romanization in multilinguality in LLMs

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:48.251462Z

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Observation 4baff3a8-682b-4ca8-b802-9cf2ac6d6944 · outbound

This paper cites ML-SUPERB: Multilingual Speech Universal PERformance Benchmark.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition ML-SUPERB: Multilingual Speech Universal PERformance Benchmark

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:48.367629Z

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Observation ff8331d9-7684-42df-9a4e-bd38a5bca8d6 · outbound

This paper cites Jiatong Shi, Shih-Heng Wang, William Chen, Martijn Bartelds, Vanya Bannihatti Kumar, Jinchuan Tian, Xuankai Chang, Dan Jurafsky, Karen Livescu, Hung yi Lee, and Shinji Watanabe.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition Jiatong Shi, Shih-Heng Wang, William Chen, Martijn Bartelds, Vanya Bannihatti Kumar, Jinchuan Tian, Xuankai Chang, Dan Jurafsky, Karen Livescu, Hung yi Lee, and Shinji Watanabe

Reference 22

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:48.461649Z

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Observation 08f4d00d-534b-4354-96bb-c7e7709d35c4 · outbound

This paper cites Igor Sz¨oke, Miroslav Sk´acel, Ladislav Moˇsner, Jakub Paliesek, and Jan ˇCernock`y.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition Igor Sz¨oke, Miroslav Sk´acel, Ladislav Moˇsner, Jakub Paliesek, and Jan ˇCernock`y

Reference 23

Resolution: verified exact; doi, observed 2026-07-31T23:20:57.160299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b81a2f74-0339-49d4-a2d1-96784e2e187b · outbound

This paper cites k2SSL: A faster and better framework for self-supervised speech representation learning.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition k2SSL: A faster and better framework for self-supervised speech representation learning

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:48.965674Z

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Unavailable: canonical work link unavailable.

Observation e25d7037-4fca-42ae-9b94-384e15daab2a · outbound

This paper cites mHuBERT-147: A compact multilingual HuBERT model.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition mHuBERT-147: A compact multilingual HuBERT model

Reference 26

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:49.106858Z

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Observation 37431f17-5301-4cd5-b9d4-80e7752feb05 · outbound

This paper cites Linear- complexity self-supervised learning for speech processing.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition Linear- complexity self-supervised learning for speech processing

Reference 27

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:49.173710Z

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Unavailable: canonical work link unavailable.

Observation a2914072-a04c-4beb-880d-1e0681699564 · outbound

This paper cites Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages

Reference 28

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:49.234557Z

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Observation 21f0b02f-db2e-4283-be82-cb267a806840 · outbound

This paper cites Efficiently Democratizing Medical LLMs for 50 Languages via a Mixture of Language Family Experts.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition Efficiently Democratizing Medical LLMs for 50 Languages via a Mixture of Language Family Experts

Reference 29

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:49.325332Z

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Observation 398d1cc1-0816-43f8-a3ae-fadd6f79597d · outbound

This paper cites Opportunities and Challenges of Large Language Models for Low-Resource Languages in Humanities Research.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition Opportunities and Challenges of Large Language Models for Low-Resource Languages in Humanities Research

Reference 30

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:49.420035Z

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Observation 33bdb0ee-20e6-47ea-b1a1-646a1d566f5e · outbound

This paper cites ByT5 model for massively multilingual grapheme-to-phoneme conversion.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition ByT5 model for massively multilingual grapheme-to-phoneme conversion

Reference 31

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:49.538974Z

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Observation 652f4ced-adb8-4851-bceb-c8ba5e6c9d5a · outbound

This paper cites (b) Duration of the dataset after segmentation.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition (b) Duration of the dataset after segmentation

Reference 32

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:49.668759Z

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Observation 3048929e-b524-43f2-887d-edf412eb9959 · outbound

This paper cites an unresolved cited work.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition Unresolved cited work

Reference 33

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:49.814480Z

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Observation 4961b7cf-317b-400a-8d35-a838aba5b5c9 · outbound

This paper cites However, constructing reliable phonetic transcriptions at the scale considered in this work (495 languages) remains impractical.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition However, constructing reliable phonetic transcriptions at the scale considered in this work (495 languages) remains impractical

Reference 34

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:49.968769Z

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Observation e7831f77-6851-4ff7-9ff9-cb6e675218ed · outbound

This paper cites Consequently, generating consistent, high-quality phoneme transcriptions across hundreds of languages is currently infeasible.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition Consequently, generating consistent, high-quality phoneme transcriptions across hundreds of languages is currently infeasible

Reference 35

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:50.102651Z

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Observation 2d23cf9d-1312-4380-bff4-519bfda2cdbc · outbound

This paper cites In contrast, frame-level routing does not exhibit a clear or consistent language-dependent grouping pattern.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition In contrast, frame-level routing does not exhibit a clear or consistent language-dependent grouping pattern

Reference 36

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:50.250185Z

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Observation ea2d9432-442c-4044-b47f-c0cc1eea0484 · outbound

This paper cites Multilingual Large Language Models and Curse of Multilinguality.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition Multilingual Large Language Models and Curse of Multilinguality

Reference 2012

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:46.840026Z

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Observation be728194-2db0-413c-9094-4e989ff1dc6e · outbound

This paper cites Language-routing mixture of experts for multilingual and code-switching speech recognition.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition Language-routing mixture of experts for multilingual and code-switching speech recognition

Reference 2013

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:48.769547Z

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Observation 83c9cfa5-d04c-463f-b964-9c8786363816 · outbound

This paper cites Omnilingual ASR: Open-source multilingual speech recognition for 1600+ languages.arXiv preprint arXiv:2511.09690,.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition Omnilingual ASR: Open-source multilingual speech recognition for 1600+ languages.arXiv preprint arXiv:2511.09690,

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:47.564151Z

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Observation 6526d9ef-6ca9-4e57-9b28-ad5c8022136c · outbound

This paper cites Sustainable self-supervised learning for speech representations.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition Sustainable self-supervised learning for speech representations

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:47.846814Z

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Observation 870be727-8386-45e5-b9d5-c2de4891100f · outbound

This paper cites Alabi, Xuechen Liu, Dietrich Klakow, and Junichi Yamagishi.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition Alabi, Xuechen Liu, Dietrich Klakow, and Junichi Yamagishi

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:45.967833Z

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Observation 43001e13-a645-499f-a587-4695668c2e35 · outbound

This paper cites PRiSM: Benchmarking Phone Realization in Speech Models.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition PRiSM: Benchmarking Phone Realization in Speech Models

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:46.424728Z

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Observation ff876484-44de-4c0a-a417-93291e5c7236 · outbound

This paper cites Dynamic language group-based MoE: Enhancing code-switching speech recognition with hierarchical routing.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition Dynamic language group-based MoE: Enhancing code-switching speech recognition with hierarchical routing

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:47.090222Z

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Observation 7b0481ec-5e12-4f85-bb93-71834bef3715 · outbound

This paper cites an unresolved cited work.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition Unresolved cited work

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:48.023495Z

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Observation e16c331f-e8ef-4bce-afb7-c56184c45523 · outbound

This paper cites Upcycling Large Language Models into Mixture of Experts.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition Upcycling Large Language Models into Mixture of Experts

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:46.956823Z

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Observation d91deb52-43cf-40cb-a45b-d209da2213b0 · outbound

This paper cites Mixtral of Experts.

MoLGE: Mixture of Language Group Experts for Efficient Scaling of Massively Multilingual Speech Recognition Mixtral of Experts

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-07-31T23:18:47.234580Z

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Pith citing papers

No inbound Pith citation observations are available.